code: def __init__(
      self,
      block,
      layers,
      relu_type="swish",
  ):
      super(ResNet, self).__init__()
      self.inplanes = 64
      self.relu_type = relu_type
      self.downsample_block = downsample_basic_block
  
      self.layer1 = self._make_layer(block, 64, layers[0])
      self.layer2 = self._make_layer(block, 128, layers[1], stride=2)
      self.layer3 = self._make_layer(block, 256, layers[2], stride=2)
      self.layer4 = self._make_layer(block, 512, layers[3], stride=2)
      self.avgpool = nn.AdaptiveAvgPool2d(1)
  
file_path: audio/examples/avsr/models/resnet.py
imports: import torch.nn
label_desc: Use image node_id 1 to create a new ResNet object from inherited base classes: nn with example: obj = ResNet(block, layers, relu_type)